Within present day communication systems, the problem of mitigating interference and noise in received signals is a common one. In particular, when a system utilizes multiple receive antennas, the task of providing an accurate interference estimate and optimized throughput becomes essential in order to provide reliable and competitive services. Due to the increased use of the available frequency spectrum, and the ever increasing number of user terminals, the co-channel and adjacent interference becomes a problem. In addition, for fading channels with a user terminal that moves, also Doppler spread becomes an important factor to consider.
Two commonly used methods of mitigating interference by combining received signals from a plurality of receiver antennas in a base station, or in a user terminal, in a communication system are interference rejection combining (IRC) and the even more common maximum ratio combining (MRC).
Interference rejection combining (IRC) enhances the transmission capacity in a communication system by mitigating undesirable co-channel/adjacent interference. This is made possible by estimating and utilizing the so-called spatial correlation of the interfering signals between multiple receiver antenna elements of a receiver. In doing so, the received interference is suppressed by spatial whitening. In the application of communication, the IRC is typically followed by receiver equalization and decoding. An alternative to IRC is maximum ratio combining (MRC) of the antenna signals. The MRC criterion serves to maximize the signal-to-noise ratio (SNR) rather than maximizing the signal-to-interference-plus-noise-ratio (SINR).
As an example, an LTE system employs reference symbols transmitted at known time/frequency resources, i.e., known pilot symbols, from which a SC-FDMA/OFDM receiver can estimate the channel and the spatial covariance matrix of the interference plus noise.
In a system as mentioned above, uplink user signals are allocated in the frequency domain by one or more groups of 12 contiguous subcarriers, i.e., one or more resources blocks. In addition, also on the downlink the resource blocks are allocated in the frequency domain but not necessarily contiguously. Hence, for both uplink and downlink the cell-interference tends to be frequency-dependent. Moreover, adjacent interference due to e.g. leakage from neighboring systems typically interfere more at the frequency band edges. Thus, also the adjacent interference tends to be frequency-dependent.
IRC can be viewed as spatially whitening of the received signals before further processing and combining the antenna signals according to e.g. the MRC criterion. The coefficients of the whitening filter are typically calculated from the estimated disturbance, i.e., the spatial covariance matrix of the interference plus noise. Different criterions such as the minimum means-square error (MMSE) and the optimum combining (OC) have been proposed to compute the IRC coefficients.
Recent research has revealed that it is beneficial to estimate IRC coefficients in the frequency domain on groups of sub carriers in order to reduce the computational complexity compared to more commonly used frequency-bin based IRC. At the same time, this enables frequency-dependent mitigation of co-channel/adjacent interference. The basic concept employs coefficient calculation with interpolation/extrapolation between successive reference symbols (pilot symbols) in order to further reduce the computational complexity.
In order to make IRC a viable solution for communication systems, the customer expects the throughput performance to be at least as good as or better than wideband MRC for interference-limited scenarios, and have similar performance for noise-limited scenarios. With ideal estimates IRC and MRC provide the same (theoretical) quality or throughput (IP) performance for noise limited scenarios. In practice, however the IRC throughput is typically less than with MRC with an implementation according to the above mentioned IRC coefficient estimation on groups of sub-carriers, for noise limited scenarios, due to at least the following issues. When there is a high Doppler frequency due to user equipment movement, the channel estimate will not reflect the actual channel. This will degrade the performance of IRC combining, as it is calculated based on the estimated channel. In addition, for situations with high SNR and high Doppler frequency, residual errors from the channel estimation will be interpreted as interference. This will cause degradations, as the IRC combining will try to suppress the (self-made) estimated interference.
This problem can to some extent be mitigated by the introduction of an MRC/IRC threshold algorithm that selects MRC/IRC dependent on the interference scenario. In brief, according to prior art [1], a receiver with both IRC and MRC functionality further comprises a threshold functionality. This threshold functionality evaluates the interference of the received signals and selects one of IRC and MRC based on the result of that evaluation. If the interference of the received signal meets or exceeds a predetermined interferences threshold, the receiver utilizes IRC to mitigate the interference e.g. the signal is determined to be interference limited. However, if the interference of the received signal does not exceed or meet the predetermined threshold the receiver utilizes MRC to mitigate the interference e.g. the signal is determined to be noise limited.
However, as already mentioned, the above mentioned prior art solution can be further improved for scenarios with high SNR and high Doppler frequencies, due to the erroneous interpretation of residual errors from the channel estimation as interference.
Due to the above-mentioned problems, there is a need for rendering the IRC/MRC threshold algorithm less sensitive to the influence of Doppler induced residual error in the channel estimates.